System and method for motor and cognitive analysis

ABSTRACT

In an example embodiment, this disclosure provides a non-transitive computer-readable medium on which are stored instructions executable by a processor, the instructions which, when executed by the processor, cause the processor to perform a method. The method includes computing, based on test performance data of a user, at least one of a performance variable characterizing cognitive functioning and a performance variable characterizing neuromotor functioning. For each of the at least one performance variable, a respective score can be computed based on the respective performance variable and based on a set of performance metrics. The method can also include outputting, via an output device, the at least one computed score.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/542,548, filed Oct. 3, 2011, entitled SYSTEM AND METHOD FOR MOTOR ANDCOGNITIVE ANALYSIS. This application also is a continuation-in-part ofU.S. application Ser. No. 13/510,683, which relates to U.S. ProvisionalPatent Application No. 61/262,662, filed Nov. 19, 2009, andPCT/US2010/057453, filed Nov. 19, 2010, the contents of each of whichare hereby incorporated by reference in their entireties.

TECHNICAL FIELD

Inventions described herein relate generally to a system and method toobjectively qualitatively quantify cognitive, motor, and cognitive-motorfunctioning.

BACKGROUND

There are various neuromotor and neurocognitive disorders includingAlzheimer's disease, Parkinson's Disease (PD), and progressivesupranuclear palsy to name a few. Neuromotor and neurocognitivedisorders affect motor function, cognitive function or both.

In order to properly treat many neuromotor and neurocognitive disorders,it is desirable to better understand or classify an individual'scondition. Accordingly, a variety of tests have been developed forvarious types of diseases and injuries. For example, one scale forassessing a patient's Parkinson's disease is the Unified Parkinson'sDisease Rating Schedule (UPDRS). Various other tests exist that areutilized by a clinician to help the clinician categorize a patient'sdisorder.

To more efficiently administer and objectively analyze results of suchtests, computerized systems for administering some of such tests havebeen proposed. U.S. Pat. No. 6,435,878 (“the '878 patent”) proposes asystem where a user's reaction time to a stimulus can be measured.However, the proposed system does not measure the quality of the user'sinteraction with the system. The system of the '878 patent alsodynamically modifies a presentation time or quantity of a stimulus forthe stimulus based on the user's performance, but does not qualitativelymodify test difficulty based on user performance.

U.S. Pat. No. 7,294,107 (“the '107 patent”) similarly refers to atesting system with which user reaction time can be measured. However,as with the '878 patent, the system does not measure the quality of theuser's interaction with the system. The system of the '107 patent alsodetermines based on user performance which tests to administer andwhether to terminate a test, but does not qualitatively modify aparticular test's difficulty based on user performance.

U.S. Pat. No. 6,517,480 (“the '480 patent”) refers to a testing systemin which a maze trace is detected and an overall time for completion ofthe test is detected, but the system does not provide for anyqualitative measurement of the user's performance of the test or formodifying testing difficulty in view of user performance.

Moreover, none of the '878, '107, and '480 patents provide a system ormethod for time-based testing of a degree of cognitive ability, nor dothey provide a system or method that presents data regarding acorrelation of test results to patient information, such as medicationsthe patient is taking and/or stimulation parameters used for Deep BrainStimulation (DBS) of the patient.

SUMMARY

This invention relates to a system and method to for motor and cognitiveanalysis.

According to an example embodiment, a computer system can include aprocessor configured to compute, based on test performance data of auser, at least one performance variable characterizing cognitivefunctioning, and at least one performance variable characterizingneuromotor functioning. For each performance variable, processor cancompute a respective score based on the respective performance variableand based on a set of performance metrics. The at least one computedscore can be output via an output device.

According to another example embodiment, a computer-implemented methodcan include receiving, by a computer processor, user position datainformative of user positions relative to an input device. The processorcan also compute a variable value based on the position data. Theprocessor can also compute, based on the computed variable, a scorecharacterizing at least one of a motor function of the user, a cognitivefunction of the user, and a cognitive-motor function of the user.

According to yet another example embodiment, a non-transitivecomputer-readable medium on which are stored instructions executable bya processor, the instructions which, when executed by the processor,cause the processor to perform a method. The method includes computing,based on test performance data of a user, at least one of a performancevariable characterizing cognitive functioning and a performance variablecharacterizing neuromotor functioning. For each of the at least oneperformance variable, a respective score can be computed based on therespective performance variable and based on a set of performancemetrics. The method can also include outputting, via an output device,the at least one computed score.

This invention also relates to systems and methods for displayinginformation derived from the underlying measurements. Such analysisand/or resulting display can help a physician or other health careprovider diagnose the patient's condition.

To facilitate use and access, the test can be implemented as anInternet-based application that can be accessed by an authorized user ata remote location via a predetermined resource locator (e.g., a URL).Additionally, by implementing the system as a web-based application,test data can be maintained (anonymously) for a plurality of patients ata central server to facilitate further analysis and research. Forexample, results of the testing for a plurality of users further can beaggregated to generate a new index for classifying movement disorders ordetermining the severity of a movement disorder, which may (or may not)be correlated with existing standards, such as the commonly used UnifiedParkinson's Disease Rating Scale (UPDRS). For example, a composite scoremay be calculated that combines both cognitive performance (e.g.,related to dwell time or set switching time, where set switching timerefers to the time taken to refocus attention from one task to another)and motor performance (e.g., related to straightness of movement), whichcomposite score may be useful for simultaneous assessment of bothcognitive and motor function. Since the measure would be captured in astandard manner across users, the measure may be used to characterize acurrent user's performance against a larger group of patients. Theclinician may use the comparative data to explore effects of variousmedical interventions and their predicted outcomes.

According to an example embodiment of the present invention, acomputer-implemented testing method may include: recording, by aprocessor, respective time information for each of a plurality ofpositions of a display device that are traced during administration of atest; determining, by the processor, a plurality of speed values and/ora plurality of velocity values based on the recorded time information;and outputting, by the processor, test result information based on thespeed and/or velocity values.

In an example method, the output information includes a score computedbased on the determined plurality of speed and/or velocity values.

The method may further include plotting the values as a graph curve, andcomparing at least one slope of the curve to at least one slope of astored curve. The score may be based on the comparison.

The method may include determining derivatives of the velocity values,and the test result information may be based additionally on thederivatives. For example, the derivatives may include accelerationvalues.

The method may include generating at least a portion of the test resultinformation by calculating an average, standard deviation, mean squareerror, and/or root mean square error of a difference of (a) thedetermined values from ideal values, or (b) derivative values of thedetermined values from ideal derivative values.

The method may include, responsive to the trace of the plurality ofpositions, recording the plurality of traced positions. Each of thedetermined values may be recorded in association with respective ones ofthe recorded plurality of traced positions.

According to an example, the recorded plurality of traced positions arerecorded at a rate of approximately 30 Hz.

According to an example, the output information includes a graph thatplots the determined values against the recorded plurality of tracedpositions.

According to an example, each of the plurality of traced positions isrecorded as a respective pair of an abscissa value and an ordinatevalue. For each pair of abscissa and ordinate values, the abscissa andordinate values are separately associated with respective ones of thedetermined values.

In an example method, the output information indicates cognitive abilityand/or motor skill of a user in response to whose movement the pluralityof positions are traced.

In an example method, the display device is part of a patient terminal,the time information is recorded at a server coupled to the patientterminal via a network, and the test result information is output at aclinician terminal coupled to the server via the network. In an exampleembodiment, the network includes the Internet.

According to an example embodiment of the present invention, acomputer-implemented testing method may include: displaying in a displaydevice a first target and a second target; responsive to user inputcorresponding to a trace of a plurality of positions in the displaydevice, which, in combination, form a path from the first target to thesecond target, recording, by a processor, respective time informationfor each of the plurality of positions; and determining, by theprocessor, and outputting, information regarding a cognitive abilityand/or a motor skill of a user based on the recorded time information.

The various methods and system components described herein may bepracticed and provided, each alone, or in various combinations.

An example embodiment of the present invention is directed to one ormore processors, which may be implemented using any conventionalprocessing circuit and device or combination thereof, e.g., a CentralProcessing Unit (CPU) of a Personal Computer (PC) or other workstationprocessor, to execute code provided, e.g., on a hardwarecomputer-readable medium including any conventional memory device, toperform any of the methods described herein, alone or in combination.The one or more processors may be embodied in a server or userterminal(s) or combination thereof. The user terminal may be embodied,for example, as a desktop, laptop, hand-held device, Personal DigitalAssistant (PDA), television set-top Internet appliance, mobiletelephone, smart phone, etc., or as a combination of one or morethereof. The memory device may include any conventional permanent and/ortemporary memory circuits or combination thereof, a non-exhaustive listof which includes Random Access Memory (RAM), Read Only Memory (ROM),Compact Disks (CD), Digital Versatile Disk (DVD), and magnetic tape.

An example embodiment of the present invention is directed to a hardwarecomputer-readable medium, e.g., as described above, having storedthereon instructions executable by a processor to perform the methodsdescribed herein, and/or for storing output data produced via executionof the methods described herein.

An example embodiment of the present invention is directed to a method,e.g., of a hardware component or machine, of transmitting instructionsexecutable by a processor to perform the methods described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a test and analysis system, according to anexample embodiment of the invention.

FIG. 2 depicts a system architecture that can be implemented for testingand analysis of motor and cognitive functions, according to an exampleembodiment of the invention.

FIG. 3 is a screen shot for a log-in screen, according to an exampleembodiment of the invention.

FIG. 4 depicts a patient's questionnaire that can be presented to apatient or clinician user, according to an example embodiment of theinvention.

FIG. 5 depicts a screen shot for another part of a questionnaire thatcan be presented to a patient or clinician user, according to an exampleembodiment of the invention.

FIG. 6 depicts a graphical user interface (GUI) that can be utilized forcalibration of a remote test device, according to an example embodimentof the invention.

FIG. 7 depicts a screen shot GUI for an introductory screen that can beutilized for initiating a test, according to an example embodiment ofthe invention.

FIG. 8 depicts a screen shot GUI that can be utilized for providinginstructions for a “seven's test”, according to an example embodiment ofthe invention.

FIG. 9 depicts a “seven's test” GUI that can be implemented on acomputer, according to an example embodiment of the invention.

FIG. 10 depicts the “seven's test” GUI of FIG. 9 illustrating the testcompleted by a user, according to an example embodiment of theinvention.

FIG. 11 depicts a screen shot GUI that can be utilized for providinginstructions for a reaction test, according to an example embodiment ofthe invention.

FIG. 12 depicts a reaction test GUI that can be implemented on acomputer, according to an example embodiment of the invention.

FIG. 13 depicts the reaction test GUI of FIG. 12 at least partiallycompleted by a patient user, according to an example embodiment of theinvention.

FIG. 14 depicts a screen shot GUI that can be utilized for providinginstructions for a computer-implemented trail making test (Part A),according to an example embodiment of the invention.

FIG. 15 depicts a trail making test (Part A) GUI that can be implementedon a computer, according to an example embodiment of the invention.

FIG. 16 depicts the trail making test (Part A) GUI of FIG. 15 partiallycompleted by a patient user, according to an example embodiment of theinvention.

FIG. 17 depicts a screen shot GUI that can be utilized for providinginstructions for a computer-implemented trail making test (Part B),according to an example embodiment of the invention.

FIG. 18 depicts a trail making test (Part B) GUI that can be implementedon a computer, according to an example embodiment of the invention.

FIG. 19 depicts the trail making test (Part B) GUI from FIG. 18partially completed by a patient user, according to an exampleembodiment of the invention.

FIG. 20 depicts a trail making test being performed on a surface of atablet personal computer (PC) by a patient user, according to an exampleembodiment of the invention.

FIG. 21 depicts test results that can be displayed to a user via amanagement user interface, according to an example embodiment of theinvention.

FIG. 22 depicts the management user interface of FIG. 21 demonstratingan example of where data can be obtained for use in assessingneurocognitive functions of a patient user, according to an exampleembodiment of the invention.

FIG. 23 depicts velocity data that can be computed for a trail makingtest (Part A), according to an example embodiment of the invention.

FIG. 24 depicts an enlarged view of a portion of the test from FIG. 23that can be generated based upon data acquired from a patient user,according to an example embodiment of the invention.

FIG. 25 depicts dwell time data computed for a plurality of targets fora trailing making test (Part A) and a trail making test (Part B) test,according to an example embodiment of the invention.

FIG. 26 depicts a screen shot for another management user interface thatcan be utilized for browsing and selecting patient test data, accordingto an example embodiment of the invention.

FIG. 27 depicts another management user interface that can be utilizedfor managing patient protocols employed during testing, according to anexample embodiment of the invention.

FIG. 28 depicts a computing environment that can be utilized forimplementing systems and methods described herein, according to anexample embodiment of the invention.

FIG. 29 is a block diagram of an analysis engine for a test and analysissystem, according to an example embodiment of the invention.

DETAILED DESCRIPTION

FIG. 1 depicts an example of a test system 10 that can be implementedaccording to an aspect of the invention. The system 10 includes a testengine 12 that includes methods and functions that are utilized toacquire data relevant to the testing process performed by the system 10.In an example embodiment, the test engine 12 may be located at a serverto which a user computing device may connect to remotely access themethods and functions of the test engine 12.

The test engine 12, for example, can include a patient informationmodule 14. The patient information module 14 can be programmed toacquire patient information that can be provided to an analysis engine16 in the form of patient data 18. The patient information can include aseries of templates or forms (e.g., an XML or other document) that canbe completed by a user using an appropriate user input device, such as akeyboard and/or mouse and/or stylus. Examples of patient informationinclude log-in information to authenticate the user with the system,such as a log-in ID and password. The patient information can alsoinclude information about a patient's current health condition as wellas information about the environment in which the patient is taking thetest. Additional information can be acquired relating to medication thatthe patient is currently taking, including names of medication, dosage,number of times per day, and the time since the last dosage. Thoseskilled in the art will appreciate various types of forms and constructsthat can be utilized to acquire and send the patient data 18 to theanalysis engine 16.

The test engine 12 also includes a calibration module 20 that isprogrammed to calibrate the system such as for remote operation in whichspecifics of the users' test equipment may be unknown. The calibrationcomponent 20, for example can be utilized to ascertain a relativetwo-dimensional size of a display or monitor on which the test is beingimplemented. For example, a graded scale can be graphically renderedonto a display, such as a series of spaced apart lines that are providedwith a corresponding normalized scale known to the programmer. Anarticle can be provided to the user of a known size (e.g., an 8½″×11″sheet of paper, a dollar bill, or credit card), which can be positionedadjacent to the scale by the user to ascertain dimensions (e.g., in boththe x and y directions) of the user's display according to size of theimage being displayed to the user via the graphical user interface 22. Auser can in turn enter the corresponding score into the system 10 ascalibration data 24 that is utilized by the analysis engine 16. Thus, byknowing the relative display size for the user's computing device,appropriate geometry and position information can be obtained from thesubsequent battery of tests to be performed. The analysis engine 16 canemploy the calibration data 24 to scale the corresponding testing dataconsistent with the user's particular test environment (e.g., displayscreen) on which the user is taking the test. Specifically, the datapresented to the user for the test and/or the test results may be scaledaccording to the calibration data. For example, accuracy (i.e., size) ofdisplayed targets and/or distances between displayed targets may bemodified according to Fitts' law in accordance with the user's testenvironment.

In an alternative example embodiment of the invention, the calibrationmay be performed by transmitting data for presentation of three or fourtargets in the user's screen, one target at each corner of the screen.The system may record a number of pixels or defined X,Y positionsbetween the targets as a representation of vertical and horizontaldistances between the targets, which distances may be used ascalibration data for scaling test data.

Alternatively or additionally, certain patient devices can bepre-configured having known configurations, such that calibration may beomitted. For example, devices having a predetermined configuration maybe registered with the system. For instance, such preregistered devicesor terminals can reside at doctors' offices, at hospitals, or otherinstitutions.

In an alternative example embodiment, differences in the display screensmay be ignored, and the test data presented to the user and the testresult may be uniform across the various test platforms.

The test engine 12 also includes a plurality of test applications (e.g.,functions or methods) 26 and 28, indicated as TEST 1 application throughTEST N application, where N is a positive integer denoting any number oftests. Each test application can be programmed in a manner to test motorand/or cognitive functions, and/or a combination of motor and cognitivefunctions, of a user.

For example, the test can be similar to known tests such as a “Seven'stest” (described in detail below with respect to FIGS. 9 and 10), atrail making test such as the trail making test parts A and B, a clockdrawing test, and a reaction-time and motor task that can be utilized totest appropriate motor and/or neurocognitive functions of the user.Other tests with which the test engine 12 maybe programmed may include acenter-out test (which assesses information processing speed (e.g.,deciding to which target to move) and motor performance (e.g., qualityof movement to a given target)), an Archimedes spiral test (to assesstremor in Parkinson's patients, where, as the patient progressesoutward, tremor intends to increase), Benton's judgment of lineorientation test (which measures visuospatial judgment in brain-injuredpatients), and tests whose complete renderings are dynamically providedas the user takes the tests. For example, a cyclical tracking test maybe provided, for which a pattern for the user to trace is provided thatincludes points rendered after the user begins to trace the pattern. Forexample, a sine wave, circle, or other pattern, which changes or movesas the user traces the pattern may be displayed.

Each test application 26 to 28 can be provided to a user computer in aninteractive manner that provides interactive graphical objects in theGUI 22, within a hardware display device, such as a computer or tabletscreen. Such interactivity can be implemented through the use of anaction script or other functions or methods that can be provided to theuser, some of which can vary according to the platform in which the testengine 12 is being implemented, for example, based on a calibration asdescribed above.

In an example embodiment, the test engine 12 can be implemented usingthe Flash platform, such as can be programmed using ADOBE® FLEX®software available from Adobe Systems Incorporated. The Flash platformhas advantages in that, for example, it has an extremely high marketpenetration and no additional software components are required to beinstalled on the user's machine, such as when the test engine 12 isaccessed remotely such as via a web browser of the user's machine.Advantageously, the FLEX® applications for each of the components of theapplications or methods 14, 20, 26 and 28 may provide a stateful clientwhere changes can occur on the display without requiring to load a newweb page. Additionally, it has been determined that such animplementation allows sufficient resolution of geometry and positiondata to be acquired such that corresponding test results can be analyzedto provide meaningful information about motor, cognitive andcognitive-motor function of the user.

Data is acquired for each test application 26 to 28 as correspondingrespective test data 30 to 32, which can be provided to and/or utilizedby the analysis engine 16. Thus, by performing a plurality of multi-parttests 26 through 28, each test can provide corresponding test data 30 to32 that can be analyzed by the analysis engine 16 to provide meaningfulinformation and results based on the test data 30 to 32.

The test data can include an indication of which test of a plurality ofdifferent tests is being performed along with an indication of theposition of graphical objects (e.g., targets) for the test as well as anindication of the position for a cursor or other pointing device that isutilized for performing the test. For example, the test application 26to 28 can employ a get_cursor_pos( )or other Application ProgrammingInterface (API) to monitor and obtain cursor position information thatis stored along with temporal information, such as the timescorresponding to the obtained cursor positions, as the test data 30 to32. The sampling of such data may be at a rate of, for example, 30 Hz.

As an example, a test application 26, 28 can display on the display aGUI having one or more targets, each as a graphical object having ashape (e.g., a circle, oval, triangle or rectangle) that encompasses orbounds a set of coordinates on the user's display device. A user canposition on the display a cursor or other graphical object having itsown object position in two-dimensional space (e.g., having X and Ycoordinates), for example, using a pointing device, such as a mouse orstylus for touch screen, or without a pointing device, such as via afinger on a touch screen. The test application 26, 28 can provideinstructions requesting the user to position the cursor/object or drawlines between two or more particular targets. The movement of the cursoron the screen relative to the known position of each of the targets(corresponding to the test data 30 to 32) can be analyzed by theanalysis engine 16.

The analysis engine 16 may include, for example, a motor calculator 34and/or a cognitive calculator 38. The calculators 34 and/or 38 may be,for example, software modules stored on a computer-readable hardwaredevice, which may be executed to perform various calculations based onthe same or different input parameters.

In an example embodiment, the motor calculator 34 is programmed todetermine a number of one or more kinematic variables based on the testdata 30 to 32. For example, the motor calculator 34 can be programmed todetermine a position of the cursor or pointer device, a velocity, anacceleration, a speed and/or a tangential acceleration for each sampleof test data acquired during a test interval. For example, thetangential acceleration may be used by the analysis engine 16 as anindication of degree of curvature in user movements.

In an example embodiment, the motor calculator 34 can also determinederivative information of the above-referenced variables, such ascorresponding to a measure of how close to the user's line between apair of targets is fitted to an ideal straight line between the pair oftargets. For example, for every data point residing on the idealstraight line between sequential targets, a distance to a correspondingpoint on the line drawn by the user can be determined. The sum of thedetermined distances between the respective points can be determined,and divided by the number of points for which the distances weredetermined to provide an average associated with the ideal line relativeto that drawn by a user. This can be repeated for a line drawn by a userbetween respective targets to provide an objective indication of theaccuracy of lines drawn.

In an example embodiment, the motor calculator 34 may further calculatea means square error by determining an average of the error squared forthe difference between the ideal and actual lines. In an exampleembodiment, the motor calculator 34 may further calculate the root meansquared error or standard deviation of the difference between the idealand actual lines, for example by calculating the square root of themeans square error. Thus, the motor calculator 34 can determine variousvalues representative of the average distance that the user's datapoints on the user's line deviate from the idea line.

In an example embodiment, average, means square error, root means squareerror, and/or standard deviation information may be similarly calculatedfor deviation, over the course of a test, per each recorded position,each separate X position and Y position, and/or on a per line basis,between speed, velocity, acceleration, tangential acceleration, etc.,between actual recorded values and ideal values for those parameters.

Other information includes whether the user has drawn crossing lines, asdescribed below with respect to FIGS. 15 and 16.

The above is not intended as an exhaustive list of calculations whichthe motor calculator 34 may perform, and other example embodimentsprovide for calculation of additional or alternative variables andparameters based on the acquired test data 30 to 32 that is sampled overtime. The results of the calculations determined by the motor calculator34 can be stored as part of analysis data 36. The analysis data 36 canalso include calibration data 24 and patient data 18, which can beutilized to improve the accuracy of the calculations by the motorcalculator 34 and the cognitive calculator 38. Alternatively,calibration data may be used, as described above, to alter theadministered test, so that results of tests administered at differentplatforms are comparable, without requiring further consideration ofdifferences between the platforms, e.g., as reflected by the calibrationdata 24.

In an example embodiment of the invention, the cognitive calculator 38is programmed to compute variables or parameters relevant to assessingcognitive function of a patient-user. For example, the cognitivecalculator 38 can compute a dwell time based on the acquired test data30 and 32. A dwell time can correspond to a time period during which acursor or other graphical object is within a given predefined boundedarea, such as can be defined as an X and Y position or range thatencompasses a displayed graphical object or target. The computed dwelltime may be used to assess a patient's set switching ability, to refocusattention from one task to another, for example, where dwell timereflects a dwell period in a first target (after initial movement to thefirst target) before moving to the next target. Dwell time may be anindicator of “cognitive freezing” in neurocognitive or other patientgroups. The cognitive calculator 38 can also calculate the reactiontime, such as corresponding to a time interval between a presentation ofa stimulus and the initiation of movement of a pointing device by a userduring a reaction test application 26, 28, which can be further utilizedby the cognitive calculator 38 to generate a score of the patient'sinformation processing capacity. In an example embodiment of theinvention, the cognitive calculator 38 may further use data output bythe motor calculator 34, e.g., representative of motor function quality,to calculate data representative of cognitive ability.

For example, an initial speed or acceleration when leaving a giventarget to move to a following target may be used as a cognitivemeasurement in certain instances. For example, if the initial phase ofmovement is relatively rapid (with high velocity and acceleration), andthe user moves to the correct target, this information may be used toconclude that the user movement was made primarily under predictive orfeedforward control (i.e., the user was very sure of where to go). Onthe other hand, if the speed or acceleration is relatively low or thereare multiple starts and stops once the user leaves the target, theinformation may be used to conclude that the patient is unsure of thetarget to which to move, indicative of a deficiency in informationprocessing speed, especially where other components of the usermovements are relatively normal or can be made relatively quickly. Itshould be understood and appreciated that certain types of calculationsmay not apply to different types of tests depending upon the mainpurpose of the test.

In an example embodiment of the invention, the analysis engine 16 canoutput results of calculations to provide corresponding analysis data36. Thus, the analysis data 36 can include results data based upon themethods and calculations performed by the motor calculator 34 and/or thecognitive calculator 38 based on test data 30 to 32 acquired for each ofthe respective test applications.

In an example embodiment of the invention, the analysis engine 16 mayinclude an index calculator 40 that is programmed to compute one or moreindices based upon the output results determined by the motor calculator34 and/or cognitive calculator 38 for a patient. For example, the indexcalculator 40 can aggregate the analysis data determined for a given setof test data acquired for a given patient to determine an index (orscore) having a value indicative of motor function for the given patientbased on the aggregate set of test data. Alternatively or additionally,the index calculator 40 can compute an index (or score) having a valueindicative of cognitive function for a patient based upon the set oftest data. Alternatively or additionally, the index calculator 40 cancompute an index (or score) having a value indicative of cognitive-motorfunction for a patient based upon the set of test data. The indexcalculator 40 can be normalized according to a known scale or index,such as the UPDRS. Alternatively or additionally, the index calculator40 can calculate a new scale that provides an indication of motor and/orneurocognitive functions for the patient. The resulting output for theindex calculation can be provided and stored as part of the analysisdata 36 for subsequent analysis, e.g., by a clinician who may access thestored analysis data 36.

In an example embodiment of the invention, the system may modify factorsused for the index calculation based on the corpus of data for aplurality of patients. For example, if a large number of users who areconsidered generally healthy perform poorly on a certain test, the testresults for that test may be modified by a low weighting factor.

In an example embodiment of the invention, as a user takes one or moretests, the system may generate analysis data 36 which indicates that thetest(s) presented to the user are too difficult or too easy for theuser. For example, where calculated scores are extremely low, the scoresmay indicate that the user is below a certain threshold level ofability, but do not finely indicate the user's level of ability belowthat certain threshold. Similarly, where calculated scores are extremelyhigh, the scores may indicate that the user's level of ability is abovea certain threshold level of ability, but do not finely indicate theuser's level of ability above that certain threshold.

Accordingly, in an example embodiment of the invention, the test engine12 further includes a module for accessing stored analysis dataconcerning a current patient and selecting one of the TEST applications1-N to next output to the user based on past performance indicated bythe accessed analysis data. For example, where the test engine 12determines from the analysis data that the user's performance is below apredetermined threshold, the test engine 12 may select a next test thatis ranked as being at a particular low difficulty level. For example,difficulty may be ranked according to target accuracy (i.e., the size ofthe displayed targets (e.g., relative to calibrated screen size)) and/ordistance between the displayed targets (e.g., relative to calibratedscreen size). For example, a test having targets at a first distancefrom each other and of a first size may be ranked as easier than anothertest of the same type having targets that are at a second distance fromeach other, longer than the first distance, and/or that are of a secondsize, smaller than the first size. In an example embodiment, the changein test difficulty may be implemented by re-administering the same typeof test as a previously administered test, with changes to the targetaccuracy and distances and thus changes in the difficulty level of there-administered test.

In an alternative example embodiment, the change in test difficulty maybe implemented by re-administering the same test or same type of test asa previously administered test, but with changes to the moving status ofat least one target. For example, an increase in difficulty may involvechanging from a stationary target to a moving target, or changing from aslow-moving target to a faster target. Similarly, a decrease indifficulty may involve changing from a moving target to a stationarytarget, or changing from a fast-moving target to a slower target.Difficulty may be ranked according to moving status.

In an alternative example embodiment, the change in test difficulty maybe implemented by selecting a different type of test, which test type isranked at a different difficulty level than that of a previouslyadministered test.

In an example embodiment of the invention, during administration of atest, the analysis engine 16 may produce part of the analysis data 36associated with the test, even before completion of the test. During thetest, the test engine 12 may access the partial analysis data 36produced for the test prior to its completion, and may modify thecurrent test during its administration based on the partial analysisdata 36. For example, during the administration of the test, the testengine 12 may enlarge previously displayed targets of the test and/orshorten the distance between the previously displayed targets and/orchange targets between moving and stationary states. Alternatively oradditionally, where the test dynamically displays targets during itsadministration, the test engine 12 may display new targets that arelarger than those previously displayed, or at distances that are shorterthan the distances between pairs of previously displayed targets, orhaving a different moving status compared to previously displayedtargets.

FIG. 2 depicts an example of a network system 50, including an examplearchitecture for performing testing, analysis and/or evaluation. In theexample of FIG. 2, the system 50 includes a system server 52 that isprogrammed to provide methods and functions for use to implement variousmethods remotely at user devices indicated at 54, 56 and 58. Each of theuser devices 54, 56 and 58 is connected to or can communicate with thesystem server 52 via a network 60. The network 60 may include a localarea network (LAN), wide area network (WAN) (e.g., the Internet) or acombination of networks, including private and public domains, as isknown in the art.

In an example embodiment, the system server 52 may include a web serverhaving a plurality of different functions and methods, each of which canbe accessed via a corresponding resource locator, such as a uniformresource location (URL). In an example, the system server 52 includes anaccess control function 64 that provides a level of security such thatonly authorized users can access various other functions and methods ofthe system. The access control function 64 can provide a log-in userinterface screen to each of the user devices 54, 56 and 58, which canrequire a user ID and password for each user for authentication. Eachuser ID and password can be associated with a corresponding level ofauthorization to selectively provide access to one or more of the otherfunctions and methods to be provided by the server system 52. While FIG.2 illustrates devices 54, 56, and 58 as separate devices, the operationsof each may be performed on a single device, but may be logicallyseparated according to the log-in information. In an example embodiment,a single set of log-in information may provide authorization for accessto operations of more than one of the shown devices 54, 56, and 58.

For example, the user device 54 can be assigned a high or unlimitedauthorization level and utilized to provide one or more management userinterfaces 66, for accessing each of the functions and methods providedby the server system 52, including accessing corresponding managementfunctions and methods indicated schematically at 67. Thus, theauthorized user of the management user interface 66 can access variousmanagement functions 67 for the patient information, browsing test dataand the like. For example, the user interface 66 may be a clinicianinterface via which a clinician may access test results for tests takenby the clinician's patients or other related information. Examples ofselected management user interface screens are shown in FIGS. 26 and 27.

The user device 56 can include a patient user interface 68 that canprovide a limited amount of access such as to the testing functions andmethods 70. For example, after logging in via the access controlfunction 64, a patient user interface 68 can be used to access the testapplications 70, which can be graphically displayed in the patient GUI.The test applications can be provided as interactive web pagesprogrammed with functions and methods for performing various tests andobtaining patient-controlled movement information from the patient-user.

The test methods 70 that are provided to the patient user device 56 viathe patient user interface can be implemented using ADOBE® FLEX® oranother similar software or platform having a high market penetration.By having a sufficiently high market penetration, substantially nosoftware needs to be installed or loaded onto an individual user'sdevice. In response to interaction with the tests provided via the testmethods 70, test data 30 to 32 may be obtained by the system server 52for storage in a central data storage 74 (described in further detailbelow). Methods of the analysis engine 16 may be performed locally atthe patient user device 56 or remotely at the system server 52.

Examples of associated graphical user interfaces associated with thetesting functions and methods that can be presented to the user areshown and described herein with respect to FIGS. 4-20.

Another user device 58 can include a research user interface 72 thatprovides access to relevant data (e.g., excluding patient identifyinginformation) such as to facilitate research and analysis of the testdata. For example, a researcher or other authorized user can access aset of test data for a plurality of patients and, in turn, performstatistical methods or other mathematical operations on the set of datato ascertain relevant information, such as correlations or likelihoods.A researcher might also utilize the analysis data to draw correlationsbetween other information entered by the user (e.g., patient data,including an identification of medications, dosage and the like)relative to test results for each of a plurality of users. Such analysiscan provide information that can be stored in the central data storage74 for subsequent usage and review by other authorized users. Forexample, correlations can be drawn between medication and test resultsand changes in test results over time, which correlations can bepresented to a physician or other authorized user via the managementuser interface 66.

Alternatively or additionally, certain patient devices can bepreconfigured having a preset authorization status, such thatauthorization would not be required. Such devices known to the systemserver 52 can access the system server 52 through the network 60 orthrough a secure local area network or other suitable connection. Forinstance, such preconfigured terminals can reside at doctors' offices,hospitals or other institutions.

In an example embodiment, regardless of the configuration anddistribution of patient user devices 56, the test data is consolidatedinto a database or other central data storage 74 that is associated withthe central system server 52.

The central data storage 74 can include raw test data 76 and resultsdata 78. While central storage 74 is shown as a single storage deviceand/or logical storage location, in an example embodiment, the raw testdata 76 may be stored separate from the results data 78, e.g., forquicker response time to results data queries.

The raw test data 76 and results data 78 can be indexed by patient andby individual test as well as include patient specific information (inan example embodiment, excluding patient identifying information otherthan perhaps a patient unique identify number) for purposes ofseparating the patient data from one patient from that of anotherpatient. As described herein, the test methods 70 and the system server52 can be programmed to perform calculations on the raw test dataacquired from a patient user interface via the testing application beingimplemented thereon.

Similarities between patients residing in a given cluster (i.e.,patients who share certain characteristics) can be utilized tofacilitate treatment and diagnosis of other patient's having similarconditions. For example, a clinician may enter information (e.g.,patient information with respect to medication (type and/or dosage),stimulation parameters (e.g., of a DBS therapy), symptoms, conditions,and/or diagnoses) via the management user interface 66, which can betagged (or programmatically linked) to the test data and results data ofthe patient, such as to augment or provide metadata that can be furtherevaluated or considered to facilitate clustering of patients andunderstanding the respective conditions. In this way, the test data fora more statistically significant population can be maintained forperforming statistical analysis of test data, which can be mined orotherwise evaluated statistically or otherwise, e.g., via the researcheruser interface, to understand the correlations of symptoms andconditions. For example, the system of the invention may be queryablefor test result data by symptom(s) and/or diagnosis, in response towhich the system may return results data 78 concerning those patientsmatching the symptom(s) and/or diagnosis, and/or averages and/or otheraggregate data of the results data 78.

In an example embodiment, the system and method of the invention mayprovide for a clinician, using the user device 54, to input a proposedchange, e.g., with respect to medication (type and/or dosage) and/orstimulation parameters (e.g., of a DBS therapy), for a particularpatient for whom patient information and test results have beenobtained. In response to a query triggered via user-selection of acommand at the user device 54, the system server 52 may search thecentral data storage 74 for patients associated with patient data andtest data similar (by a predetermined degree) to those of the particularpatient. The server may further search for those of the patients whohave been subjected to a change similar to that proposed for theparticular patient and for whom subsequent test results data have beenobtained. The server may output for display at the user device 54 anaverage of such subsequent test results, thereby indicating to theclinician an expected change in the particular patient's condition withthe proposed change, measured in terms of expected change in testresults.

Alternatively or additionally, the system may output a medical conditioncategory corresponding to the average of such subsequent test results.For example, different intervals of test scores may be associated inmemory with different categories of cognitive and/or motor skills. Thecategory under which the average of the subsequent test results fallsmay be output. Alternatively or additionally, the expected direction ofchange to the medical condition classification may be output, e.g.,whether the cognitive and/or motor skills are expected to improve ordecline.

FIGS. 3 through 27 show example screen shots or other graphics forpresentation in a user interface, to provide a general understanding ofthe algorithms and functionality that can be implemented by the systems10 and 50 shown and described with respect to FIGS. 1 and 2.

FIG. 3 depicts an example of a screen shot 100 including a GUI element102 that can be utilized for access control into the system, asdescribed in detail above. The GUI element 102 includes user entryfields 104 that can be utilized for obtaining a user name and accesscode for authorized use of the system. Graphical buttons or othersgraphical interface elements 106 can be provided for submitting orclearing information with respect to the user entry fields 104.

FIG. 4 depicts an example of a screen shot 110 including an example of aGUI element 112 for obtaining information pertaining to a user's generalhealth condition, state of mind and environment in which the test isbeing taken. For example, the questions may include: “How many hours ofsleep did you get last night?”; “What is your level of fatigue on ascale of 0-10?”; “On a scale from 1 to 5 how noisy is yourenvironment?”; “Where are you currently taking the test right now?”Associated with this or other questions can be a drop down context menu114 that can be utilized by the user to identify and select one of apredetermined number of responses. After answers to the question(s) havebeen entered, a user can hit a continue user interface element (agraphical button) 116 to continue.

FIG. 5 depicts another screen shot example 120 that can be utilized toobtain information about medication that a given patient may be taking.The screen shot 120 includes a GUI element 122 having a variety of dropdown context menus that can be utilized to identify medication(s),dosage, number of times per day the medication(s) is taken, and time(s)since last dosage of the medication(s). After the particulars associatedwith a given medication have been entered via the drop down contextmenus 124, a user may enter them into the system via an add userinterface element 126. Similarly, an entry can be deleted or removed byselecting it with a cursor or other user interface element and in turnhitting a delete user interface element 128. After all medications havebeen appropriately entered into the medication form GUI element 122, auser can continue to the next phase of the testing process by hitting auser interface element or button 130. The medication information can beprogrammatically associated with test data to allow correlations to bedetermined, such as described herein. In an example embodiment, aclinician may enter some or all of the medication and/or other therapyinformation into the system.

FIG. 6 depicts an example of a screen shot 134 demonstrating acalibration GUI 136 that can be implemented for calibrating a remoteuser's computing device in a horizontal direction, according to anexample embodiment of the invention. The calibration GUI 136 presentsthe user a scale 138 having a plurality of spaced apart markings orindicia, which are numbered consecutively in the example of FIG. 6 fromzero to thirty. The calibration GUI 136 presents instructions to theuser to fold a 8.5″×11″ sheet of paper in half and place the shorter endof the folded sheet of paper adjacent the scale 138 with the one of thelonger sides against the zero, and to enter the number closest to theother of the longer sides in a user entry dialogue box 140. The numberentered into the dialogue box 140 relative to the actual size of thepaper can be utilized to determine a size or dimensions of the displayarea presented on a user screen during the testing process. A similarcalibration can be utilized in a vertical direction on a user screensuch that both the horizontal and vertical dimensions can be known suchthat the results from the testing can be scaled appropriately.

FIG. 7 depicts an example of a “welcome” screen shot that can bepresented to the user to inform the individual that a test is about tobegin and identify some additional information about the types of thetest and how they will proceed. It should be understood that a fewpractice screens and tests can be implemented before beginning an actualtest to familiarize a user with the testing process.

FIG. 8 depicts an example of an instruction GUI 146 that can be providedbefore performing a first test. FIGS. 9 and 10 depict an example of GUI150 that includes a plurality of targets 152 for use in performing a“seven's test”, for which a user is instructed to draw between targets apath having a shape similar to the number “7”, for testing cognitiveand/or motor skill. Each of the targets can be graphically constructed,as a graphical object that encompasses a region in the X/Y coordinatesof a patient's graphical interface, such as in a screen. The GUI 150corresponds to an example of a traditional “seven's test” in which auser is instructed to connect the dots using a pointing device such as amouse, stylus, touch screen or the like. In the example of FIG. 9 threetargets numbered numerically 1, 2, 3 are presented on the screen. A useris instructed to connect the targets 1 to 2 to 3 to draw a shape similarto the number “7”. The system may record test data in association withperformance of the test. The test data may include, for example, theposition and temporal information of the path taken for connecting thetargets. FIG. 10 shows an example of an outcome of a patient havingconnected target positions 1 and 2 but not target positions 2 and 3. Toindicate the successful connection of target positions 1 and 2, thesystem has highlighted targets 1 and 2, in contrast to target 3 which isnot highlighted. Referring back to FIG. 1, the test data acquired fromFIG. 9 can include an identification of the position of each of thetargets, a path taken by the patient for connecting or attempting toconnect the targets, and/or temporal information associated with thepath.

Thus, the information obtained with respect to the test outcome shown inFIG. 10 may include the coordinates of each of the targets 152 as wellas the coordinates (or position) of the cursor or other pointing elementduring the test as the cursor or other pointing element moves betweenthe respective targets and forms a corresponding line or path 154.

FIG. 11 depicts an example of an instruction GUI 158 that can beprovided before performance of a second test.

FIGS. 12 and 13 depict an example of a GUI 160 that can be provided inconnection with performing a reaction time test with subsequentmovement, such as a center-out test, for testing, e.g., cognitiveability. Thus, the GUI 160 includes a plurality of targets, includingthe center target 162 and a plurality of outer targets 164 incircumscribing relation relative to the center target. The center-outtest can be performed to test reaction time of the user by displayingone of the outer targets 164 in a contrast color relative to the othertargets 162 and 164 and in turn storing the time interval fromdisplaying the contrasted target on the GUI 160 to the time the userbegins to move a pointing device for connecting the central target 162to the contrasted outer target 164. Additional information can beobtained during the process, including the position over time of thecursor relative to each of the respective graphical renderings of thetargets, e.g., representing a path taken by the user between the centertarget 162 and the outer targets 164, and/or the corresponding times.

In FIG. 13, a partially completed center-out test is depicted showingone of the targets 166 having a contrast color relative to the othertargets thereby designating the intended target for connection betweenthe center target 162 and the contrast target 166. The center-out testcan be performed such that different ones of the outer targets areselected in a predictable or random order one or more times.

FIG. 14 depicts an example of another instruction GUI 168 that can bepresented to a user for providing instructions for performing a thirdtest, including such as shown and described with respect to FIGS. 15 and16.

FIGS. 15 and 16 depict an example of a test GUI 170 that can be utilizedfor performing a trail making test (Part A), for testing cognitiveand/or motor skill. The trail making test (Part A) implemented via theGUI 170 may be used to assess both motor and cognitive informationconcurrently. For instance, a plurality of targets 172 are distributedacross the display area provided by the GUI 170. In the example of FIGS.15 and 16, the targets are numbered from 1 to 24 and the user (asinstructed by the instruction GUI 168 of FIG. 14) is to connect thetargets in a sequential order. The test engine can populate the displayarea for the GUI 170 in a pseudo random fashion such that each of thesequential targets can be interconnected by an ideal straight linewithout crossing a line interconnecting any other sequential targets.Thus, in addition to obtaining the position, velocity, speed and/oracceleration information, crossing lines can also be identified toprovide a further indication of a patient's motor and cognitivefunction.

FIG. 16 depicts an example in which a patient has connected the firstfive targets with lines going from target 1 to target 2 to target 3 totarget 4 and to target 5. Thus, from the example tests of FIGS. 15 and16 information corresponding to the position of the cursor that isutilized to draw each line connected between sequentially numberedtargets can be recorded and stored as test data in memory (e.g., localor associated with a server). In addition to the position data, temporaldata can be obtained with each sample as well. Thus, the position andtime data can then be provided as test data to the analysis system forevaluation, such as shown and described in further detail below.

Also depicted in FIG. 16 is a diagrammatic view of a line used in ananalysis that can be performed to characterize a degree of error, e.g.,by calculating an average error, a mean square error, or a root meansquare error, for each of a plurality of respective linesinterconnecting sequential targets 172 in the GUI 170. For example,referring to targets 2 and 3, this can be performed, for example, bycomparing the relative positions of points along an ideal straight line250 connected between targets 2 and 3 relative to a line segment 252drawn by a patient (e.g., responsive to user-controlled movement with apointing device) between the same respective targets. For instance, thesame number of equally spaced sample points can be populated along thelength of each line segment 250 and 252 and a corresponding means squareerror can be computed for differences between the sets of sample points.For example, the error values recorded for the sample points can besquared, then summed together, and then divided by the number of samplepoint pairs to provide the mean square error of the patient's line 252relative to the ideal line segment 250. Those skilled in the art willunderstand and appreciate various types of estimators that can beutilized to compute a measure of how close the user's line 252 is to thefitted ideal (straight) line 250 between targets, such as including thesample mean, sample variance, analysis of variance, root mean squareerror, standard deviation as well as linear regression techniques.

For example, the resulting mean square error can further be utilized tocompute a root means square error by taking the square-root of the meansquare error for each of the line segments between targets. The rootmeans square error thus can provide essentially an average measure ofdistance of the user's data points on the line 252 from correspondingpoints on the ideal line 250.

FIG. 17 depicts an example of an instruction GUI 180 that can beprovided for instructing a user for a trail making test (Part B) testsuch as shown in FIGS. 18 and 19, for testing cognitive and/or motorskill.

FIGS. 18 and 19 depict an example of a GUI 182 that can be presented toa user in connection with performing and recording informationassociated with a trail making test (Part B). The GUI 182 presents aplurality of targets positioned in a display area according toapplication data determined by a corresponding test application. In theexamples of FIGS. 18 and 19, the targets are circles, each of whichdefines a bounded region having a corresponding set of coordinates. Inthe display GUI 182, a portion of the targets, indicated at 184, haveletters ranging consecutively from A through H and another correspondingportion of the targets, indicated at 186, have numbers rangingconsecutively from 1 through 13. Those skilled in the art willunderstand that the test engine can be programmed to automaticallygenerate any arrangement of targets consistent with the format of thetrail making test (Part B), which arrangement may be part of the testdata provided to the analysis engine 16.

The trail making test (Part B) implemented by GUI 182 may be used toassess both motor and cognitive information concurrently. For instance,the instructions (e.g., via the instruction GUI 180 of FIG. 17) specifythat a user-patient is to alternate between consecutive sequentialletters and numbers by connecting respective targets with straightlines, similar to what is shown in FIG. 19 up to letter E, beginningwith the lowest number to the lowest letter, to the second lowestnumber, to the second highest letter, etc. Thus, FIG. 19 shows anexample outcome of a test in which a user has used a cursor having aposition that can be tracked via the corresponding API. The system isconfigured to dynamically render a graphical depiction of a line ontothe display GUI 182 in response to movements of the cursor, for example,via a corresponding pointing element, such as a mouse, stylus or touchscreen. Information associated with the position and times associatedwith the positions, representing times for each of the movements, can berecorded for subsequent analysis and evaluation as described herein.

FIG. 20 depicts an example embodiment in which the user computing devicefor performing a test is implemented as a tablet personal computer (PC).Thus, in this example a user holds a stylus (similar to a pen) on acorresponding touch screen for drawing interconnecting lines betweentargets, such as is shown in FIG. 18. It is understood that a user coulduse the user's fingers to draw the interconnecting lines.

FIG. 21 depicts an example of analysis data that can be generated anddisplayed in a GUI 190 as a function of test data acquired from arespective test. The resulting analysis data can be presented in avariety of formats, which may be selected by a user. In the GUI 190, aplurality of different plots are shown for depicting differentinformation that can be computed based upon the acquired position andrespective time data for a given test. Each of the plots in the top rowindicates position information, the middle row of plots indicatesvelocity information and the bottom row indicates accelerationinformation for a given test. The position data can be correlated intocorresponding velocity and acceleration information by analysis ofchange over time of the X and Y coordinates of the cursor obtained fromthe samples recorded during a test. In the example of FIG. 21, the GUIdepicts analysis data for a “seven's test” such as shown and describedwith respect to FIGS. 9 and 10. The GUI 190 can be presented via amanagement user interface 66 or researcher user interface 72 foranalysis and evaluation by an authorized user.

By way of example, the plot 192 depicts X position versus Y position,thereby showing the graphical object as a pair of interconnected linesegments in a relative coordinate system based upon user input with acorresponding pointing device, representing the path the user tookbetween the targets of the “seven's test.” A representative plot 194shows the X data of plot 192 plotted as a function of time, and plot 196shows the Y data of plot 192 plotted as a function of time.

A plot 198 depicts the velocity information corresponding to the changesin the X,Y positions plotted in plot 192 over the time period in whichthe changes occurred, i.e., during the test. Plot 200 depicts velocityin the X direction with respect to time such as by taking the changebetween plotted positional points in plot 194 over the plotted time inwhich such change occurred. Similarly, plot 202 depicts velocity of theY direction with respect to time such as by taking the change betweenplotted positional points in plot 196 over the plotted time in whichsuch change occurred.

Similarly, FIG. 23 depicts a plot 230 of velocity as a function of time(cm/sec) that can be obtained from data acquired from a trail makingtest (Part A) implemented according to an aspect of the invention. Anenlarged view of a portion 232 of the waveform formed by the plot 230 isdepicted in FIG. 24 at 240.

Referring again to FIG. 21, another set of plots 204, 206 and 208 depictthe acceleration for each of the respective curves. For instance, theplot 204 displays a plot of acceleration versus time, such as by takingthe change in velocity values of plot 198 over the corresponding timeperiod in which such change occurred. The plot 206 corresponds to theacceleration in the X direction versus time such as by taking the changein velocity values of plot 200 over the corresponding time period inwhich such change occurred. Similarly, the plot 208 displays a plot ofacceleration in the Y direction versus time, such as by taking thechange in velocity values of plot 202 over the corresponding time periodin which such change occurred.

The separate data concerning the movement in the X and Y directions,respectively, e.g., one or more of plots 194, 196, 200, 202, 206, and208, may be used, for example, to characterize skill with respect todifferent directions.

As noted above, the index calculator 40 may calculate a scorecharacterizing a test taker's performance on one or more administeredtests. In an example embodiment of the invention, the analysis engine 16may compare an overall curve shape of one or more of the types of graphsshown in FIG. 21, e.g., which plot velocity and/or acceleration, tostored graph shapes. For example, the shape of a plotted velocity oracceleration may be compared to a stored smooth bell-shaped curve, whichmay be considered to represent ideal motion by a healthy person whentaking a test. The analysis engine 16 may score the graphs of the testtaker's motion, such that the closer the shapes of the graphs to thestored graph shapes, the higher the score. Similarly, the analysisengine 16 may determine the extent (with respect to number and/ordegree) to which the graph(s) include spikes, where such spikes may beused as indications of low quality movement including significant and/ormany corrective and/or tremor-like motions.

The graph shape score(s) may be used, for example, by the indexcalculator 40, to calculate the index, which may be stored and output,for example, via the management user interface 66. It is noted that theindex may be based on a number of factors. In an example embodiment,different factors, e.g., including the graph shape score, may bemultiplied by respective weighting values, for example, depending onranked significance with respect to the overall index.

By way of further example, FIG. 22 is a reproduction of the GUI 190shown in FIG. 21 in which selected portions of position and kinematicdata have been identified by circles 220 corresponding to relevant datathat can be utilized by the cognitive calculator 38 for computing dwelltime. For example, dwell time can correspond to an amount of time that acursor or other user-controlled graphical interface element resideswithin a bounded region, such as a defined border of a target. Suchbounded regions can be identified in the testing data according toposition data (e.g., X and Y coordinates) for each of the targetspopulating a test GUI. The identified regions for which dwell time iscalculated can be identified by identifying the X and Y positionscorresponding to each time during which no change occurs in the X and Yposition or a period in which there is no velocity (e.g., from plot198).

FIG. 25 depicts example plots 2050 and 2052 of dwell time that can becomputed for a trail making test (Part A) and a trail making test (PartB), respectively. The abscissa corresponds to target number displayed inthe trail making tests, and the ordinate corresponds to the percentageof the overall time of the duration of the administered tests in whichthe cursor dwelled in the corresponding target. As described above, thedwell time corresponds to a time during which a cursor/pointing objectis within a given pre-defined X-Y position range that encompasses adisplayed target. Thus, the dwell time can be determined by correlationof position information (e.g., indicating that the cursor is within abounded target) and velocity information (e.g., indicating that thecursor is either not moving or is moving within the bounded target at arate that is below a predetermined threshold). It will be appreciatedthat motor function information can also be acquired concurrently withcognitive data represented by dwell time by computing and analyzingcorresponding kinetic information. For example, in PD patients, tremorpredominantly occurs when the patient is in a resting condition. Thatis, when the patient's hand, for example, is purposefully moving, thereis little, if any, tremor, while, when the patient's hand is notpurposefully moving and is in an essentially resting position, there maybe significant tremor, e.g., at a substantially constant 3-8 Hzfrequency. Accordingly, the dwell time information may be used as anindicator of which data is significant for measuring tremor in PDpatients. For example, the system may determine a measure for tremorfrom data corresponding to where there was a determined dwell period, inwhich the user's hand was essentially in a resting position. Thisconcurrent kinetic information can be employed to assess motor function(e.g., the patient could have some small movements during this time,especially if they have tremor) while cognitive function (e.g.,pertaining to information processing and set switching) during this timeis also analyzed.

In an example embodiment of the invention, the system and method may beused to administer and obtain data for certain tests used to measureonly motor function, e.g., related to finger tapping or tapping betweentwo points. In an example embodiment of the invention, the system andmethod may be used to administer and obtain data for certain tests usedto measure only cognitive function, e.g., the Mini Mental State Exam orRaven's Progressive Matrices tests.

FIG. 26 depicts an example of a management GUI 260 that can be utilizedto provide access to test data by a user having an appropriate level ofauthorization. Each set of test data can be associated with a patientvia name or other identifying information. As shown in the GUI 260,there can be any number of raw data elements for a given patient, whichmay generally depend on the test or tests that have been conducted. Eachset of raw data, for example, can correspond to a separate set of testdata for a given one of the tests or phases (or repetition) of a giventest.

FIG. 27 depicts a GUI 270 that can be utilized for managing protocolssuch as through a management user interface 66 implemented in a system.The protocols management GUI 270 can be utilized, for example, foridentifying testing protocols being utilized for a given patient testprocess. In the example of FIG. 27, the GUI includes selection interfaceelements 272 that can be utilized to identify protocols set for apatient, such as indicating whether a deep brain stimulator was on oroff during the respective tests or the medications and/or dosage thereofadministered to the patient at the time of the respective tests. A user,such as a clinician, thus can select a set of protocols associated witha given patient to help understand the effect a given condition hasrelative to the set of test data acquired for each patient during agiven test session.

For instance, these protocols can be implemented and corresponding setsof test data evaluated to ascertain the effects on various conditionssuch as whether a DBS is on during the test or off as well as whether apatient is on their medication at a prescribed dose or not, and theeffect of such a condition on the performance of a test. Those skilledin the art will understand various other protocols and combinations ofprotocols that can be utilized for specifying patient control parametersassociated with a given set of tests.

In view of the foregoing, it will be appreciated that systems andmethods have been described that can be implemented to provide a batteryof cognitive and motor tests to remotely assess neurological disorderssuch as neurocognitive and neuromotor disorders such as, for example,PD, Alzheimer's disease, multiple sclerosis, dementia, amyotrophiclateral sclerosis (ALS), Parkinsonian syndrome, trauma-induced braininjury, stroke and multiple systems atrophy(MSA). The systems andmethods enable the testing to be performed remotely by a patient-user,and the collection of data in a central data repository, such as toprovide access to such information by a clinician and to facilitatefurther research.

In view of the foregoing structural and functional description, thoseskilled in the art will appreciate that portions of the invention may beembodied as a method, data processing system, or computer programproduct. Accordingly, these portions of the invention may take the formof an entirely hardware embodiment, an entirely software embodiment, oran embodiment combining software and hardware, such as shown anddescribed with respect to the computer system of FIGS. 1 and 2.Furthermore, portions of the invention may be a computer program productincluding a hardware computer-readable storage medium having computerreadable program code on the medium. Any suitable computer-readablestorage medium may be utilized including, but not limited to, static anddynamic storage devices, hard disks, optical storage devices, andmagnetic storage devices.

Certain embodiments of the invention have been described herein withreference to block illustrations of methods, systems, and computerprogram products. It will be understood that blocks of theillustrations, and combinations of blocks in the illustrations, can beimplemented by computer-executable instructions. Thesecomputer-executable instructions may be provided to one or moreprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus (or a combination ofdevices and circuits) to produce a machine, such that the instructions,when executed by the processor, implement the functions specified in theblock or blocks.

These computer-executable instructions may also be stored incomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory result in an article of manufacture including instructions whichimplement the function specified in the flowchart block or blocks. Thecomputer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

In this regard, FIG. 28 illustrates one example of a computer system 500of the type that can be utilized to implement one or more embodiments ofthe systems and methods described herein for testing and analyzing motorand cognitive function of a patient. The computer system 500 can beimplemented on one or more general purpose networked computer systems,embedded computer systems, routers, switches, server devices, clientdevices, various intermediate devices/nodes and/or stand alone computersystems. Additionally, the computer system 500 or portions thereof canbe implemented on various mobile or portable clients such as, forexample, a laptop or notebook computer, a personal digital assistant(PDA), and the like.

The system 500 may include a computer 502, which may function, forexample, as any of the user devices 54, 56, and 58 and/or the server 52.The computer 502 may include a system bus 508 may include any of severaltypes of bus structures, including, for example, a memory bus or memorycontroller, a peripheral bus, and a local bus using any of a variety ofconventional bus architectures such as peripheral component interconnect(PCI), video electronics standards association (VESA), Microchannel,industry standard architecture (ISA), and extended industry standardarchitecture (EISA), to name a few. The system memory 506 may includeread only memory (ROM) 510 and/or random access memory (RAM) 512. Abasic input/output system (BIOS), containing the basic routines thathelp to transfer information between elements within the computer 502,such as during start-up, may be stored in ROM 510.

The computer 502 also may include, for example, a hard disk drive 514, amagnetic disk drive 516 (e.g., a floppy drive), e.g., to read from orwrite to a removable disk 518, and an optical disk drive 520 (e.g., aCD-ROM drive), e.g., for reading from or writing to a CD-ROM disk 522 orother optical media. The hard disk drive 514, magnetic disk drive 516,and optical disk drive 520 are connected to the system bus 508 by a harddisk drive interface 524, a magnetic disk drive interface 526, and anoptical disk drive interface 528, respectively. The drives and theirassociated computer-readable media provide nonvolatile storage of data,data structures, computer-executable instructions, etc. for the computer502. Although the description of computer-readable media above refers toa hard disk, a removable magnetic disk and a CD, it should beappreciated by those skilled in the art that other types of media whichare readable by a computer, such as magnetic cassettes, flash memorycards, digital video disks, Bernoulli cartridges, and the like, may alsobe used in the exemplary operating environment 500, and further that anysuch media may contain computer-executable instructions for performingthe methods of the invention.

A number of program modules may be stored in the drives and RAM 512,including an operating system 530, one or more application programs 532,other program modules 534, and program data 536. The operating system530 in the computer 502 could be any suitable operating system orcombinations of operating systems. The application programs 532, otherprogram modules 534, and program data 536 can cooperate to provide motorand cognitive testing on a patient computer device, such as shown anddescribed above. Additionally, application programs 532, other programmodules 534, and program data 536 can be used for computation of anindication of motor, cognitive or a combination of motor and cognitivefunctions of a patient based on the testing data, such as shown anddescribed above.

A user may enter commands and information into the computer 502 throughone or more user input devices, such as a keyboard 538 and a pointingdevice (e.g., a mouse 540). Other input devices (not shown) may includea microphone, a joystick, a game pad, a scanner, touch screen, or thelike. The mouse or other pointing device can be utilized to perform apoint-and-click action, which includes the action of a computer usermoving a cursor to a certain location on a screen (point) and thenpressing a mouse button, usually the left button (click), or otherpointing device. Such point-and-click can be used with any number ofinput devices varying from mice, touch pads, keyboards, joysticks,scroll buttons, and roller balls. The information associated with suchpoint and click operations can be provided (e.g., to a central server)as part of the test data for each of the respective tests, such asdescribed herein.

These and other input devices are often connected to a processing unit504 through a serial port interface 542 that is coupled to the systembus 508, but may be connected by other interfaces, such as a parallelport, a game port or a universal serial bus (USB). A display device 544,such as a monitor, is also connected to the system bus 508 via aninterface, such as a video adapter 546. Other display devices, such asspeakers, printers, etc. may be provided instead of or in addition tothe monitor.

The computer 502 may operate in a networked environment using logicalconnections to one or more remote computers 560. The remote computer 560may be a workstation, a server computer, a router, a peer device, orother common network node, and typically includes many or all of theelements described relative to the computer 502, although, for purposesof brevity, only a memory storage device 562 is illustrated in FIG. 28.The logical connections depicted in FIG. 28 may include a LAN 564 and/ora WAN 566. Such networking environments are commonplace in offices,enterprise-wide computer networks, intranets, and the Internet.

When used in a LAN networking environment, the computer 502 is connectedto the LAN 564 through a network interface or adapter 568. When used ina WAN networking environment, the computer 502 typically includes amodem 570, or is connected to a communications server on an associatedLAN, or has another circuitry arrangement for establishingcommunications over the WAN 566, such as the Internet. The modem 570,which may be internal or external, is connected to the system bus 508via the serial port interface 542. In a networked environment, programmodules depicted relative to the computer 502, or portions thereof, maybe stored in the remote memory storage device 562 (and/or locally). Itwill be appreciated that the network connections shown are exemplary andother arrangements for establishing a communications link between thecomputers 502 and 560 may be used.

Another example embodiment of a system and methods relating to theassessment of cognitive and neuromotor functioning will now bedescribed. The approach can be utilized to aggregate performancevariables that characterize cognitive and neuromotor functioning of apatient, each of which can involve one or more tests and correspondingtest data.

Analysis Engine

FIG. 29 depicts an example of an analysis engine 17 that may be used asan alternative to the analysis engine 16 in FIG. 1. The analysis engine16 may include at least one of a cognitive functioning calculator 33 anda neuromotor functioning calculator 35. Each of the respectivecalculators can compute performance variables characterizing arespective function of the user based on test data, collectivelydemonstrated at 31, which can be stored in memory, such as can beobtained in response to user interactions with a device used to performthe test, such as disclosed herein. When implemented with the testengine 12 of FIG. 1, the test engine 12 may provide forcognitive-related, and neuromotor-related test data 17 to be transmittedto or otherwise made accessible by the analysis engine 17 for analysis.

The analysis engine thus can combine test results from cognitive andneuromotor domains. The cognitive domain may include functions such asmemory/recall, information processing ability and set switching.Cognitive functioning may be evaluated using a Sport ConcussionAssessment Tool (SCAT) test (which is a standard questionnaire test forconcussion injuries) and testing working memory, set-switching ordelayed recognition. Additionally or alternatively, cognitivefunctioning can be evaluated using one or more of a sevens test, a trailmaking test, a clock drawing test, a center-out test, an Archimedesspiral test, a judgment of line orientation test or the like, such asshown and disclosed herein in relation to FIGS. 1-27. Thus, thecognitive functioning can be evaluated according one or more of thecognitive and/or neuromotor testing and analysis approaches shown anddescribed above.

The neuromotor domain may include reaction time and coordination.Neuromotor functioning may be evaluated by testing reaction time, suchas disclosed herein. Examples of reaction time tests can include simplereaction time (SRT) and choice reaction time (CRT). For example, SRT mayinvolve displaying an image and instructing the patient to press abutton as soon as the image is displayed. CRT may involve displaying animage in one of a plurality of display locations (e.g., a left side or aright side of the display) and instructing the user to select thecorrect display location (e.g., touching the image when the image isdisplayed on a touch screen).

In an example embodiment of the invention, the calculators 33/35 areprogrammed to compute variables or parameters relevant to assessing thefunctions of their respective domains based on corresponding test data17. For example, the neuromotor functioning calculator 35 may computeone or more variables relating to SRT or CRT, e.g., the duration betweenwhen a stimulus is displayed and when the patient inputs a validresponse.

The index calculator 39 may be programmed to compute one or more indices(e.g., also referred to herein as scores) based upon the output resultsdetermined by each of the calculators 33/35 for a patient. For example,the index calculator 39 can aggregate the analysis data determined for agiven set of test data acquired for a given patient to compute an index(or score) having a value indicative of postural stability for the givenpatient based on the aggregate set of test data (e.g., gyroscope datamay be aggregated with accelerometer data to determine postural sway).Alternatively or additionally, the index calculator 39 can computeindices (or scores), each value of which is indicative of one of a SCATor SCAT2 test (e.g., a SCAT score), working memory, set-switching,delayed recognition, SRT or CRT. The resulting output for the indexcalculation can be provided and stored as part of analysis data 41 forsubsequent analysis, e.g., by a clinician who may access the storedanalysis data 41. The analysis data 41 may be input to a visualizationmodule 43 for subsequent display, as disclosed hereinabove (see, e.g.,FIGS. 1-27).

What have been described above are examples and embodiments of theinvention. It is, of course, not possible to describe every conceivablecombination of components or methodologies for purposes of describingthe invention, but one of ordinary skill in the art will recognize thatmany further combinations and permutations of the invention arepossible. For example, the dimensions and configurations of the targetsand the types of user-controlled movement task each patient isinstructed to perform can vary from the particular examples shown anddescribed herein.

What is claimed is:
 1. A computer system, comprising: a computerprocessor; and a user input device via which the processor is configuredto receive user position data informative of user positions relative tothe input device; wherein the processor is configured to: compute, basedon the position data, a variable value; and compute, based on thecomputed variable, a score characterizing at least one of a motorfunction of the user, a cognitive function of the user, and acognitive-motor function of the user.
 2. The system of claim 1, wherein:the processor outputs via a display device graphical test objects; thecomputation of the variable value is based on a relationship of the userpositions relative to the test objects.
 3. The system of claim 2,wherein the processor is configured to determine a size of the displaydevice based on input from the user, and to scale the display of thetest data according to the determined size.
 4. The system of claim 1,wherein the processor computes separate scores respectivelycharacterizing motor function and cognitive function.
 5. The system ofclaim 1, wherein the processor computes a composite score characterizinga cognitive-motor function.
 6. The system of claim 1, wherein thecomputation of the score includes a weighting based on performance of aplurality of patients of a patient population.
 7. The system of claim 1,wherein the variable value is computed based on kinematic data obtainedfrom the position data.
 8. The system of claim 7, wherein the processoris configured to compute an error value indicative of a differencebetween the kinematic data and ideal kinematic data, the variable valuebeing based on the computed error value.
 9. The system of claim 1,wherein the processor is configured to compute an error value based on adifference between a line drawn to connect two test objects and an idealline connecting the two test objects, the line drawn being determinedbased on the position data.
 10. The system of claim 1, wherein theprocessor is configured to compute a dwell time corresponding to a timeinterval that the position data indicates a position to remain within apredefined bounded area, and the score is based on the computed dwelltime and characterizes cognitive function.
 11. The system of claim 1,wherein the processor is configured to compute, based on the positiondata, a reaction time between presentation of a stimulus and aninitiation of a movement, and the score is based on the computedreaction time and characterizes cognitive function.
 12. The system ofclaim 1, wherein the position data is obtained during administration ofa test, and the processor is configured to select, from a plurality oftests, a second test to administer based on a relationship between thecomputed score and respective difficulties of the plurality of tests.13. The system of claim 1, wherein the score is updated duringadministration of a test during which the position data is obtained, andthe system is configured to adjust a difficulty of the test based on thescore and prior to completion of the administration of the test.
 14. Thesystem of claim 1, wherein the system is configured to: receive an inputof a proposed change in medical treatment for the user; search a patientdatabase for patients with clinical characteristics and scores similarto those of the user; search the patient database for those of thesimilar patients who have been subjected to a change similar to theproposed change; and based on data stored in association with thepatients subjected to the similar change, determine an expected change,in response to the proposed change, in at least one of the score for theuser and medical condition classification for the user.
 15. The systemof claim 1, wherein the user position data is informative of userpositions relative to the input device during administration of at leasttwo of a sevens test, a trail making test, a clock drawing test, areaction time and subsequent movement task test, a center-out test, anArchimedes spiral test, a judgment of line orientation test, and a testwhose complete renderings are dynamically provided as the user takes thetest.
 16. The system of claim 1, wherein the input device is one ofattached to and held by the user during administration of a test thatprovides the user position data.
 17. The system of claim 1, wherein thecomputed score characterizing a cognitive function of the user iscomputed, the computation being based on test data obtained via at leastone of a Sport Concussion Assessment Tool (SCAT) test, a working memorytest, a set-switching test and a delayed recognition test.
 18. Thesystem of claim 1, wherein the computed score characterizing a motorfunction of the user is computed, the computation being based on dataobtained via at least one of a simple reaction time (SRT) test and achoice reaction time (CRT) test.
 19. A computer-implemented methodcomprising: receiving, by a computer processor, user position datainformative of user positions relative to an input device; computing, bythe processor and based on the position data, a variable value; andcomputing, by the processor and based on the computed variable, a scorecharacterizing at least one of a motor function of the user, a cognitivefunction of the user, and a cognitive-motor function of the user.
 20. Anon-transitive computer-readable medium on which are stored instructionsexecutable by a processor, the instructions which, when executed by theprocessor, cause the processor to perform a method, the methodcomprising: computing, based on test performance data of a user, atleast one of a performance variable characterizing cognitive functioningand a performance variable characterizing neuromotor functioning; foreach of the at least one performance variable, computing, based on therespective performance variable and based on a set of performancemetrics, a respective score; and outputting, via an output device, theat least one computed score.